Search Results (9,245)

Routine precision oncology requires realistic benchmarks for tumor-agnostic eligibility signals observed in heterogeneous comprehensive genomic profiling (CGP) pathways. We performed a retrospective descriptive analysis of anonymized aggregated nationwide Center for Cancer Genomics and Advanced Therapeutics (C-CAT) data in Japan, including 97,343 CGP-tested cases summarized across five routine CGP platforms and categorized into 12 prespecified organ groups for analysis. The primary strict approved set endpoint was the case-level union of MSI-H, TMB-H, NTRK fusion/rearrangement, RET fusion/rearrangement, and ERBB2 amplification; the expanded practical set endpoint additionally included ALK fusion/rearrangement and BRAF V600E. The primary strict approved set endpoint was observed in 14,005 cases (14.4%), and the expanded practical set endpoint in 15,911 cases (16.3%), adding 1906 cases and increasing the observed rate by 2.0 percentage points. Signals varied across organ groups and platform/specimen contexts. TMB-H and ERBB2 amplification numerically dominated the primary set signal, whereas NTRK and RET fusion/rearrangement remained rare. These observed frequencies should be interpreted as case-level implementation signals surfaced through routine CGP rather than assay superiority evidence, biological prevalence estimates, or treatment-benefit data. This nationwide, platform-aware benchmark supports practical interpretation of tumor-agnostic eligibility signals in routine CGP practice in Japan. Full article

Background: Pancreatic ductal adenocarcinoma (PDAC) has dismal survival, and vascular invasion is strongly associated with dissemination and poor outcomes; however, its molecular basis remains unclear. Methods: Transcriptomic and clinical data from The Cancer Genome Atlas-Pancreatic Adenocarcinoma (TCGA-PAAD) cohort were integrated with Genotype-Tissue Expression (GTEx) normal pancreas data. Vascular invasion-associated candidate genes were identified using subgroup-specific differential expression filtering. A three-gene prognostic signature was constructed using Cox and least absolute shrinkage and selection operator (LASSO) regression and validated in an independent PACA-AU cohort. Nucleoporin 35 (NUP35) was functionally evaluated by shRNA knockdown, phenotypic assays, endothelial assays using conditioned medium, and Western blotting of extracellular signal-regulated kinase (ERK)-vascular endothelial growth factor A (VEGFA) signaling. Results: We identified 172 vascular invasion-associated candidate genes and developed a three-gene model comprising NUP35, GMNN, and KLK11. The model stratified TCGA patients into risk groups with significantly different overall survival (OS; log-rank p = 0.014) and good predictive performance, with areas under the receiver operating characteristic curve (AUC) of 0.659, 0.722, and 0.796 for 1-, 3-, and 5-year OS, respectively. Consistent trends were observed in PACA-AU. Risk group transcriptomes were enriched for proliferative and tumor progression programs. Among the signature genes, NUP35 was prioritized because higher NUP35 expression was associated with poorer survival and positively correlated with VEGFA expression. NUP35 knockdown suppressed malignant phenotypes, reduced endothelial migration and tube formation, and decreased phosphorylated ERK and VEGFA without altering total ERK levels. Conclusions: A vascular invasion-related three-gene signature enables prognostic stratification in PDAC. NUP35 is associated with malignant and pro-angiogenic phenotypes and may regulate angiogenic activity partly through ERK-VEGFA signaling, supporting its potential as a prognostic biomarker and candidate therapeutic vulnerability. Full article

Sellar tumors, including pituitary neuroendocrine tumors (PitNETs), craniopharyngiomas, and rare malignant entities, represent a heterogeneous group of lesions characterized by complex interactions within the tumor microenvironment (TME). In recent years, extracellular vesicles (EVs) have emerged as key mediators of intercellular communication, playing a crucial role in tumor progression, invasion, and therapeutic resistance across multiple cancer types. Despite growing interest in EV biology, their role in sellar tumors remains poorly defined due to limited direct experimental evidence. This review provides a conceptual and translational framework for understanding EV-mediated communication in the context of sellar region tumors. We summarize current knowledge on EVs biogenesis, molecular cargo, and mechanisms of uptake, and discuss how these vesicles may influence tumor behavior through modulation of proliferation, angiogenesis, extracellular matrix (ECM) remodeling, and immune responses. Particular attention is given to PitNETs and craniopharyngiomas, integrating available evidence with insights derived from related tumor models. We further explore the potential of EVs as minimally invasive biomarkers and therapeutic tools and highlight the major technical and biological challenges that currently limit clinical translation. By identifying key knowledge gaps and future research directions, this review aims to guide further investigation into the role of EVs in sellar tumor biology. Full article

Cyst-predominant anterior mediastinal lesions are commonly attributed to benign thymic cysts. However, thymomas—the most common thymic epithelial tumor—may rarely present as a predominantly cystic mass with only a small solid component, posing a diagnostic challenge. The World Health Organization (WHO) classifies thymomas according to the morphology of tumor epithelial cells and the degree of lymphocytic infiltration, a schema that correlates with biological behavior and prognosis. Unlike low-risk subtypes, high-risk thymomas frequently require multimodal treatment because of their more aggressive clinical course. MRI has increasingly been utilized as a problem-solving modality for indeterminate lesions identified on CT. In particular, diffusion-weighted imaging (DWI) with apparent diffusion coefficient (ADC) measurement has emerged as a potentially useful imaging biomarker for predicting histologic subtypes of thymic epithelial tumors. We report a case of a WHO type B3 thymoma presenting as a predominantly cystic anterior mediastinal lesion, in which MRI findings suggested the possibility of a high-risk subtype. The imaging and corresponding histopathologic findings are presented in this paper. Full article

Background/Objectives: This study aimed to explore the potential value of narrow-band-imaging (NBI)-derived mean optical intensity (MOI) in monitoring the progression of oral squamous cell carcinoma (OSCC), from the normal oral mucosa through epithelial dysplasia to invasive carcinoma. We compared differences in the NBI MOI among distinct pathological stages, so as to provide preliminary evidence for its clinical application in auxiliary diagnosis and progression assessment for OSCC. Methods: A total of 40 human oral mucosal specimens (15 normal, 15 oral leukoplakia, 10 OSCC) were enrolled for NBI image acquisition and MOI measurements. A 4-nitroquinoline-1-oxide (4NQO)-induced mouse OSCC model (n = 34) was used to dynamically record MOI changes across different pathological stages. A syngeneic tongue tumor mouse model (n = 16) was further established to evaluate whether MOI could reflect tumor formation and growth. All MOI values were quantified using ImageJ software with standardized region-of-interest (ROI) selection and background correction. Results: In clinical samples, MOI values decreased progressively from the normal mucosa (129.6 ± 5.991 arbitrary units (a.u.)) to oral leukoplakia (OLK) subgroups, including mild dysplasia (104.6 ± 3.757 a.u.) and moderate-to-severe dysplasia (91.77 ± 4.345 a.u.), and further to OSCC (54.41 ± 14.40 a.u.). In the 4NQO model, the MOI of the lingual mucosa was highest in the healthy control group (167.3 ± 10.05 a.u.) and gradually declined with increasing dysplasia severity, reaching the lowest level at the OSCC stage (48.67 ± 10.07 a.u.). In the syngeneic tumor model, the MOI was significantly lower in tumor-bearing mice than in healthy controls (47.85 ± 10.44 a.u. vs. 119.7 ± 14.20 a.u., p < 0.001). Receiver operating characteristic (ROC) analysis demonstrated good diagnostic performance of the MOI in distinguishing healthy tissue from cancerous lesions. Conclusions: NBI-derived MOI may quantitatively reflect the dynamic alterations of the oral mucosa during oral carcinogenesis and could represent a potential biomarker enabling the non-invasive, repeatable early evaluation and dynamic monitoring of OSCC. Full article

Epithelial ovarian cancer (EOC) remains one of the most lethal gynecologic malignancies, largely owing to advanced-stage presentation, high rates of relapse, and the eventual emergence of therapeutic resistance. Despite the transformative success of immune checkpoint inhibitors (ICIs) across multiple solid tumors, their clinical impact in ovarian cancer has been comparatively modest. This literature review provides a comprehensive synthesis of recent advances in ICI strategies for ovarian cancer (OC), with particular emphasis on phase II and III clinical trials evaluating programmed cell death protein 1 (PD-1), programmed death-ligand 1 (PD-L1), cytotoxic T-lymphocyte–associated protein 4 (CTLA-4), and T cell immunoglobulin and mucin-domain-containing-3 (TIM-3)-directed therapies. Accumulating evidence indicates that PD-1/PD-L1 monotherapy yields limited clinical activity in unselected OC populations, with low objective response rates and minimal survival benefit. Dual checkpoint blockade with PD-1 and CTLA-4 inhibitors demonstrates enhanced antitumor activity, particularly in clear cell ovarian carcinoma (CCOC), albeit at the expense of increased immune-related toxicity. Large randomized trials incorporating ICI into first-line chemotherapy or maintenance settings have largely failed to improve outcomes in biomarker-unselected cohorts. Available evidence demonstrates that combinatorial approaches integrating ICI with anti-angiogenic agents, PARP inhibitors, or neoadjuvant chemotherapy provide modest benefit in selected molecular and histologic subgroups. Early-phase investigations of TIM-3–targeting strategies further expand the immunotherapeutic landscape, although clinical efficacy remains preliminary. Current evidence underscores that OC is not uniformly responsive to immunotherapy and that rational combination strategies, biomarker-driven patient selection, and improved understanding of tumor immune microenvironment heterogeneity are essential to unlocking the full therapeutic potential of ICI in this disease. Full article

Breast cancer remains the most frequently diagnosed malignancy among women worldwide, while metabolic dysfunction-associated steatotic liver disease (MASLD) represents the leading cause of chronic liver disease, reflecting a global burden of metabolic dysfunction. Increasing evidence suggests that MASLD is associated with breast cancer development and progression; however, whether this relationship reflects an independent effect of hepatic metabolic dysfunction or the broader metabolic environment remains uncertain. This review synthesizes current epidemiological, clinical, and mechanistic data linking hepatic metabolic dysfunction to breast carcinogenesis. Population-based studies consistently demonstrate an association between hepatic steatosis and increased breast cancer incidence, particularly in postmenopausal and metabolically vulnerable populations, as well as poorer oncological outcomes. Mechanistically, MASLD promotes a systemic pro-tumorigenic environment through interconnected pathways, including insulin resistance, hormonal dysregulation with increased estrogen bioavailability, chronic inflammation, oxidative stress, lipid metabolic reprogramming, and gut–liver axis disruption. Hepatokines, particularly fibroblast growth factor 21 (FGF21), emerge as key mediators of tumor progression and potential biomarkers of metabolic vulnerability, while Fetuin-A and angiopoietin-like protein 8 (ANGPTL8) further support the liver’s endocrine role in oncogenic signaling. Preclinical evidence highlights fatty acid oxidation as a metabolic dependency in aggressive breast cancer subtypes, suggesting novel therapeutic targets. Despite consistent associations, causality remains unproven. Future prospective studies are needed to determine whether targeting metabolic dysfunction can improve breast cancer prevention and outcomes. Full article

Immune checkpoint receptors (ICRs) play a pivotal role in modulating antitumor immunity and have become central targets in the immunotherapy of genitourinary (GU) malignancies. This review provides a comprehensive overview of the fundamental mechanisms of ICR signaling, the expression and pathophysiological roles of these receptors in GU cancers (kidney, bladder, prostate, testicular, and penile), and the evolving therapeutic landscape. Key ICRs, including PD-1, CTLA-4, LAG-3, TIM-3, and TIGIT, orchestrate complex signaling cascades that can lead to T-cell exhaustion and tumor immune evasion. Their expression varies significantly across GU cancer types, histological subtypes, and tumor stages, influencing prognosis and therapeutic response. Immune checkpoint inhibitors (ICIs) reinvigorate antitumor immunity by disrupting these inhibitory pathways and remodeling the tumor microenvironment (TME); however, resistance mechanisms (primary, adaptive, and acquired) and immune-related adverse events (irAEs) pose significant clinical challenges. Established biomarkers such as PD-L1 expression, tumor mutational burden (TMB), and microsatellite instability (MSI)/deficient mismatch repair (dMMR) status guide ICI use, but their predictive power has limitations. Consequently, emerging tissue-based (e.g., immune cell signatures, multiplex IHC/IF, spatial transcriptomics), liquid biopsy-based (e.g., ctDNA, CTCs, exosomes), and imaging-based (radiomics, AI-driven analysis) biomarkers are under active investigation to refine patient selection and monitor treatment efficacy. The therapeutic armamentarium is rapidly expanding with novel ICIs targeting new receptors, bispecific antibodies, and innovative combination strategies involving ICIs with chemotherapy, targeted therapies, radiotherapy, and other immunotherapies. Furthermore, ICIs are increasingly explored in neoadjuvant, adjuvant, and maintenance settings. This review highlights the dynamic progress in understanding ICR biology and its clinical translation, emphasizing the ongoing efforts to develop more personalized and effective immunotherapeutic strategies for patients with genitourinary tumors. Full article

Dysregulated microRNA (miR) expression has emerged as a potential prognostic tool in head and neck squamous cell carcinoma (HNSCC), but the clinical value of miR-34a remains unclear. This systematic review, meta-analysis, and trial sequential analysis (TSA) evaluated the association between tumor tissue miR-34a expression and survival outcomes in HNSCC. Following a protocol registered in PROSPERO (n. CRD420251238772), PubMed/MEDLINE, Scopus, ScienceDirect, CENTRAL, Google Scholar, and grey literature sources were searched for studies reporting overall survival (OS) or disease-free survival (DFS) stratified by miR-34a expression in HNSCC or its subsites. Hazard ratios (HRs) were extracted directly or reconstructed from Kaplan–Meier (KM) curves using the Tierney method, supported by a dedicated Python application (KM2HR). Four retrospective studies, corresponding to six study/site-specific cohorts and 318 patients, met the inclusion criteria. For OS (four cohorts), the fixed-effects model yielded a pooled HR of 2.25 (95% CI 1.48–3.41) for low versus high miR-34a expression, indicating worse survival in the low-expression group. However, the random-effects model attenuated the association (HR 1.32, 95% CI 0.32–5.54), with substantial heterogeneity (I² ≈ 77%). For DFS (two studies), the fixed-effects model suggested poorer outcomes with low miR-34a (HR 2.92, 95% CI 1.24–6.88), whereas the random-effects model reversed the direction of effect with extremely wide confidence intervals (HR 0.19, 95% CI ≈ 0.00–129.34; I² = 91%). TSA for OS (accrued information size 225 patients; estimated power ≈66%) crossed the monitoring boundary but did not reach the a priori information size, supporting only a tentative signal. A bioinformatic exploration of the TCGA HNSCC cohort (n = 522) showed a non-significant trend towards worse OS with low miR-34a (HR 1.24, 95% CI 0.93–1.65) and was excluded from pooling. Overall, low tumor miR-34a expression appears to be associated with poorer OS, but the evidence is limited by retrospective design, small sample size, and marked heterogeneity. miR-34a is a promising biomarker for prognostic stratification in HNSCC, yet larger, prospective, site-specific studies with standardized assays, pre-defined cut-offs, and appropriate adjustment for HPV status and clinical covariates are required before clinical implementation can be recommended. Full article

Background: Immunohistochemistry (IHC) plays a central role in subtyping of muscle-invasive bladder cancer (MIBC), yet conventional semi-quantitative scoring lacks objectivity and scalability. Automated digital pathology offers potential solutions, but requires robust, marker-specific validation against expert consensus scoring. Methods: We developed and internally validated an automated digital pathology pipeline for continuous IHC H-score quantification using QuPath (v0.6.0-arm64). Tissue microarrays (TMAs) were generated from transurethral resection of bladder tumor (TURBT) specimens from a cohort of patients with MIBC treated at Vancouver General Hospital. Cell detection was performed using StarDist (v0.9), followed by automated intensity-based H-score calculation for four epithelial IHC marker stains (CK14, CK20, CK5/6, and Uroplakin II). H-scoring was then restricted to tumor epithelium by object-level classification using a supervised tumor/non-tumor classifier trained on pathologist-reviewed annotations. Automated scores were compared with consensus scores from three blinded pathologists using Pearson correlation, linear regression, intraclass correlation coefficients (ICC), and Bland–Altman analysis. Results: Automated H-scores demonstrated strong agreement with pathologist consensus across all four markers. CK14 showed near-perfect agreement (ICC ≈ 0.99) with minimal bias and narrow limits of agreement. CK20 also showed high agreement (ICC ≈ 0.95). CK5/6 and Uroplakin II demonstrated slightly lower agreement (ICC ≈ 0.92 to 0.93) with mild proportional bias. Across markers, the automated pipeline preserved a broad H-score range, with range ratios of 0.96 to 0.99. Conclusions: This study establishes a robust, methods-forward pipeline for automated continuous IHC H-scoring in MIBC. The internally validated framework provides a scalable foundation for external cohort testing and future clinical outcome-associated biomarker analyses. Full article

Brain tumors in older adults are difficult to diagnose and manage due to nonspecific symptoms, overlapping with neurodegenerative diseases such as dementia, and significant tumor heterogeneity. Although molecular markers such as IDH1/2 mutations, MGMT promoter methylation, TERT alterations, and 1p/19q co-deletion have improved glioma classification and prognostic assessment, current care still relies on invasive tissue biopsies, which limit longitudinal monitoring and may not fully capture tumor complexity because of sampling bias, assay variability, and limited accessibility. Liquid biopsy offers a promising alternative that enables the detection of tumor-derived DNA, RNA, proteins, and extracellular vesicles, supporting earlier diagnosis and real-time monitoring of disease progression and treatment response. However, liquid biopsy for brain tumors is not yet clinically definitive due to low biomarker abundance, lack of standardization, and limited validation, and therefore, it cannot replace tissue diagnosis. Ongoing research focuses on multi-analyte biomarker panels, improved assay standardization, and integration with imaging and tissue-based data. In parallel, artificial intelligence and machine learning are advancing the field by integrating multi-omics and radiomic data to enhance detection, classify tumors, and predict key molecular alterations, supporting the emerging framework of radiogenomics. Together, these developments are driving a shift toward more precise and dynamic approaches to brain tumor diagnosis and management, with relevance for improving outcomes in older adults with brain cancer. Full article

Early cancer detection using minimally invasive biomarkers remains a significant challenge, particularly in early-stage disease, where circulating tumor DNA is often below the limit of detection. Extracellular vesicles (EVs), which are actively secreted by viable cancer cells and carry tumor-associated proteins, represent a promising alternative target for liquid biopsy. In this study, we developed EV-finder^®, a conceptual framework for the direct detection of EV-associated proteins in serum using proximity extension assay (PEA) technology. Unlike conventional EV-based analytical methods that require prior EV isolation or enrichment, the EV-finder approach enables direct profiling of EV-associated proteins from small serum volumes without an EV isolation step, thereby simplifying the analytical workflow while preserving EV-derived molecular information. Using serum samples from patients with five cancer types (n = 193) and independent healthy controls (n = 138), we established a two-step supervised machine learning framework for cancer detection and tissue-of-origin prediction. The screening model demonstrated promising discriminative performance, with an AUC of 0.985, sensitivity of 0.929, and specificity of 0.957. Notably, no false positives were observed in an external Japanese control cohort, whereas 4 of 29 Korean control samples were classified as cancer-positive. Analysis of EV-associated protein profiles identified both pan-cancer and cancer-type-specific signatures, supporting their value for multi-cancer detection. Collectively, these findings demonstrate the potential feasibility of direct detection of EV-associated proteins from serum using PEA technology and highlight its potential as a scalable and minimally invasive strategy for multi-cancer screening. Full article

Thyroid cancer (TC) is the most common endocrine malignancy, with a steadily rising global incidence. Despite most cases having a favorable prognosis, a subset of patients develops aggressive, recurrent, or radioiodine-refractory disease, demonstrating the need for improved molecular biomarkers and targeted therapies. The Forkhead box P (FOXP) transcription factors (FOXP1–FOXP4) have appeared as important regulators of tumor biology, yet their roles in thyroid cancer remain incompletely defined. This review summarizes current bioinformatic, experimental, and clinical evidence regarding FOXP expression patterns, molecular mechanisms, and clinical relevance in TC. FOXP3 and FOXP4 are mainly associated with aggressive clinicopathological features, including extrathyroidal invasion, lymph node metastasis, and distant metastases, and may serve as markers of poor prognosis. The most explored FOXP3 contributes to immune evasion and radioiodine resistance by suppressing sodium iodide symporter expression and regulating tumor-associated immune responses. FOXP4 promotes tumor progression by activating key oncogenic signaling pathways and regulating non-coding RNAs. In contrast, evidence indicates that FOXP2 primarily acts as a tumor suppressor in TC by inhibiting cell proliferation and promoting apoptosis, although it may show context-dependent functions. FOXP1, though less well studied, is also suggested to have tumor-suppressive effects in some studies, and demands additional investigation in TC. Collectively, current evidence suggests that FOXP family members may represent promising diagnostic, prognostic, and therapeutic biomarkers in thyroid cancer, although further validation in large clinical cohorts and mechanistic studies is still required. Full article

Objective: The aim of this study was to evaluate the expression of PD-L1, PD-1, CD3, CD4, and CD8 in tumor tissues of patients with head and neck squamous cell carcinoma from southern Poland, and to assess their prognostic value in relation to disease-free survival (DFS), taking into account HPV16 status and other clinical, pathological, and demographic factors. Material/Methods: This study included 155 unselected patients with head and neck squamous cell carcinoma (HNSCC) from the southern Poland region, who underwent diagnostic evaluation and surgical treatment. Formalin-fixed, paraffin-embedded (FFPE) tissue blocks were obtained from these centers. The patients were treated at the Maria Skłodowska-Curie National Research Institute of Oncology, Kraków Branch, between 1991 and 2014, with treatment approaches including induction therapy (preoperative), adjuvant therapy (postoperative), or definitive chemoradiotherapy with cisplatin. Protein expression was assessed using immunohistochemistry and quantified (TPS, CPS, H-score). Relationships between expression levels and epidemiological, clinical, and histopathological features were analyzed. Results: The results show that PD-L1 overexpression was associated with worse DFS, whereas overexpression of PD-1, CD3, CD4, and CD8 correlated with improved DFS. These associations were statistically significant in the HPV16-negative subgroup, while no such correlations were found in HPV16-positive patients. In multivariate analysis, independent prognostic factors associated with improved DFS included HPV16 infection, absence of PD-L1 overexpression, overexpression of CD4 and CD8, and combined chemoradiotherapy with cisplatin. Conclusions: These findings confirm the prognostic relevance of PD-L1, PD-1, and T-cell markers in HNSCC, particularly in HPV16-negative patients, and support further research into the use of these biomarkers in personalized treatment strategies. Full article

Background/Introduction: Prostate cancer (PCa) is the most commonly diagnosed malignancy among men and remains a major cause of cancer-related mortality worldwide. We aimed to evaluate whether radiomic features extracted from normal endocrine organs, combined with clinical variables, could predict clinical progression in patients with PSMA-negative prostate cancer. Materials and Methods: In this retrospective study, 101 men with biochemically recurrent prostate cancer and negative [¹⁸F]DCFPyL PET/CT scans were included. Radiomic features were extracted from the adrenal glands, thyroid, the hypothalamus–pituitary complex, and testes. Post-imaging variables were excluded to prevent temporal data leakage. Models were developed using a stratified train/test split framework with preprocessing and feature selection performed exclusively within the training subset prior to evaluation on the held-out test set. Performance was evaluated using AUC, accuracy, sensitivity, specificity, and Brier score, while bootstrap confidence intervals and DeLong analysis were used for statistical assessment. Results: Multimodal fusion models integrating CT radiomics, PET radiomics, and clinical variables demonstrated the strongest predictive performance. The highest-performing model combined TESTIS_CT and TESTIS_PET radiomics with clinical variables, achieving an AUC of 0.758 (95% CI: 0.653–0.849). Clinical-only models remained highly competitive, with the best configuration achieving an AUC of 0.727 (95% CI: 0.618–0.833). PET + clinical and CT + clinical models achieved AUC values of up to 0.733 and 0.729, respectively, while imaging-only models demonstrated substantially lower discrimination. Although endocrine organ radiomics numerically improved predictive performance and specificity, DeLong analysis demonstrated no statistically significant improvement beyond clinical variables alone. Discussion: These findings suggest that endocrine organ radiomics may provide complementary system-level imaging biomarkers reflecting tumor–host interactions in PSMA-negative prostate cancer. However, their incremental clinical value remains modest. Conclusions: Endocrine organ radiomics combined with clinical variables demonstrated promising predictive performance in PSMA-negative prostate cancer, particularly in multimodal fusion models. Nevertheless, the added value beyond clinical variables alone was not statistically significant and requires validation in larger independent cohorts. Full article